Image-based Virtual Try-on via Channel Attention and Appearance Flow

Virtual try-on is an image generation task for changing characters' clothes while preserving the characters' and the cloth's original attributes. Existing methods usually apply the traditional appearance flow method, which is susceptible to complex body postures or occlusions, leading to unclear texture of target clothing or distorted limbs of characters. We apply a StyleGAN-based(generative adversarial network) flow generator to estimate appearance flow, which provides more global information to overcome the issue. Additionally, more local information is captured to refine the appearance flow by adopting the channel attention mechanism. Qualitative and quantitative experiments demonstrate that our model can generate more realistic images.